Search: “error handling” Category: Code and Tech — 10 articles.
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10 articles in Code and Tech · matching “error handling”
Discover vital secure coding practices tailored for remote and distributed development teams working with sensitive information, ensuring data integrity and compliance.
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Discover how to build a powerful AI coding agent by assembling multiple layers, from orchestration to reflection, to handle complex, real-world development sessions effectively.
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Discover the hidden dangers of relying solely on AI to write your software tests. Learn about coverage blind spots, false confidence, and how to effectively integrate AI into your testing strategy.
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The daily life of a developer is rapidly evolving from manual typing to sophisticated prompting, critical reviewing, and strategic steering of AI tools. Explore how this shift impacts productivity, skill sets, and the future of software development.
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Here is a quick breakdown of what the article covers: * **The Shift:** Traditional RAG follows a rigid, linear pipeline (`Retrieve -> Generate`). **Agentic RAG** introduces dynamic, self-correcting loops using the LLM as a reasoning engine within a state machine. * **Why LangGraph:** Unlike standard DAG (Directed Acyclic Graph) pipelines, LangGraph supports **cyclic workflows** (loops), enabling self-evaluation, error handling, and tool re-invocations. * **Core Architecture:** Built around three elements: * **State:** A shared dictionary (`AgentState`) tracking history and variables across steps. * **Nodes:** Python functions that execute steps (agent reasoning, evaluation, web search). * **Edges:** Conditional routes that direct execution flow based on state evaluation. * **Production Best Practices:** Always enforce **iteration limits** to prevent infinite loops, use **lightweight models** for evaluators to reduce latency, and keep evaluation separate from tool execution.
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Learn best practices for integrating AI coding agents into your development workflow safely. Discover strategies for version control, code review, and prompt engineering to leverage AI without compromising code quality.
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Unlock the full potential of AI code generation with these proven prompting techniques. Learn how to craft effective prompts that deliver accurate, high-quality, and production-ready code.
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Explore the rising trend of 'vibe coding' and its appeal for rapid development, contrasting it with the crucial demands of maintainability, scalability, and robustness required for production-ready software.
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Learn the essential principles of writing clean code to improve readability, reduce bugs, and build more maintainable and scalable software projects. This guide covers practical tips for every developer.
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Learn essential TypeScript patterns for building production-ready APIs, focusing on Data Transfer Objects (DTOs), robust data validation, and consistent, safe error handling strategies.
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